ML Engineer (NLP)

We're looking for an AI Engineer to join our AI and Data team, where you'll build and ship AI-powered products that directly improve customer service operations - from support chatbots and voice assistants to automated call analysis pipelines.

Your Future Tasks

• Design, develop, and maintain AI-powered chatbots for customer support, handling real customer queries at scale

• Build and improve voice processing pipelines — automatic speech recognition (ASR), text-to-speech (TTS)

• Develop agent-based systems using frameworks like Pydantic-AI or LangChain to automate customer service workflows

• Integrate LLMs into production services for tasks such as script compliance checking, call summarization, and intent classification

• Build and operate microservices that communicate via Kafka, expose REST APIs, and store artifacts in S3

• Experiment with prompt engineering approaches, evaluate model outputs against labeled data, and iterate on accuracy metrics

• Collaborate with the customer service and collections teams to understand business processes and translate them into AI solutions

• Own your products end-to-end — from research and prototyping through deployment, monitoring, and measuring economic impact

What We Expect

• Strong Python skills — this is our primary language for AI/ML services

• Basic understanding of machine learning concepts and hands-on experience with ML frameworks

• Experience with NLP: text classification, named entity recognition, semantic similarity, or related tasks

• Familiarity with LLM APIs (OpenAI, Anthropic, or similar) and prompt engineering techniques

• Experience building and deploying backend services (REST APIs, async processing, message queues)

• Comfort working with AWS services (S3, SageMaker, RDS, EKS)

• Understanding of CI/CD practices and containerized deployments

• Ability to work independently, move fast, and ship iteratively — our team values startup speed and MVP-first thinking

Nice to Have

• Experience with agent frameworks such as Pydantic-AI, LangChain, or similar orchestration tools

• Hands-on experience with ASR, TTS, or other voice/speech technologies

• Experience with GitOps workflows (Terraform, Flux) for infrastructure management

• Background in building customer-facing chatbots or voice assistants

• Familiarity with Kafka-based event-driven architectures

• Experience with multilingual NLP

• Knowledge of monitoring and observability tools (Grafana, Splunk)